Create README.md

README.md

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+---
+license: mit
+datasets:
+- DFKI-SLT/tacred
+language:
+- en
+metrics:
+- f1
+library_name: transformers
+pipeline_tag: text-classification
+
+# Optional. Add this if you want to encode your eval results in a structured way.
+model-index:
+- name: re_bert-base_tacred
+  results:
+  - task:
+      type: relation-classification             # Required. Example: automatic-speech-recognition
+      name: Relation Classification             # Optional. Example: Speech Recognition
+    dataset:
+      type: DFKI-SLT/tacred           # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
+      name: TAC Relation Extraction Dataset          # Required. A pretty name for the dataset. Example: Common Voice (French)
+      config: revisited      # Optional. The name of the dataset configuration used in `load_dataset()`. Example: fr in `load_dataset("common_voice", "fr")`. See the `datasets` docs for more info: https://huggingface.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name
+      split: test        # Optional. Example: test
+    metrics:
+      - type: f1         # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 0.7985       # Required. Example: 20.90
+        name: test/f1         # Optional. Example: Test WER
+        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+---